scholarly journals Results of matched‐field processing of low‐frequency Arctic under‐ice data

1989 ◽  
Vol 86 (S1) ◽  
pp. S105-S105
Author(s):  
E. Livingston ◽  
O. Diachok
1998 ◽  
Vol 06 (01n02) ◽  
pp. 269-289 ◽  
Author(s):  
Purnima Ratilal ◽  
Peter Gerstoft ◽  
Joo Thiam Goh ◽  
Keng Pong Yeo

Estimation of the integral geoacoustic properties of the sea floor based on real data drawn from a shallow water site is presented. Two independent inversion schemes are used to deduce these properties. The first is matched-field processing of the pressure field on a vertical line array due to a projected source. The second approach is the inversion of ambient noise on a vertical array. Matched-field processing has shown to be successful in the inversion of high quality field data. Here, we show that it is also feasible with a more practical and less expensive data collection scheme. It will also be shown that low frequency inversion is more robust to variation and fluctuation in the propagating medium, whereas high frequencies are more sensitive to mismatches in a varying medium. A comparison is made of the estimates obtained from the two techniques and also with available historical data of the trial site.


2000 ◽  
Vol 08 (02) ◽  
pp. 271-284 ◽  
Author(s):  
M. A. AINSLIE ◽  
R. M. HAMSON ◽  
G. D. HORSLEY ◽  
A. R. JAMES ◽  
R. A. LAKER ◽  
...  

An iterative matched field processing scheme is described for efficient inversion of geoacoustic parameters in shallow water using a vertical receiving array at three frequencies in the range 50–500 Hz. The method relies on the assumption that the acoustic data are sensitive to different geoacoustic parameters at different frequencies. First an exhaustive 2D search is carried out at high frequency to determine initial estimates for density and sound speed. A second 2D search follows at an intermediate frequency to determine sediment attenuation and sound speed gradient. An iteration is carried out over these first two phases until these four parameters converge. In a third phase, the low frequency data are used to search for the remaining unknown parameters (primarily sediment thickness, substrate density and substrate sound speed) with a differential evolution algorithm. Finally all three phases are repeated iteratively, in principle until a complete converged solution (a self-consistent set of all inverted parameters) is found, although for practical reasons the search is terminated before convergence is demonstrated. Tests on synthetic data are reported demonstrating the accuracy and stability of the method. Initial results for measured data are also presented.


Author(s):  
K. Hama

The lateral line organs of the sea eel consist of canal and pit organs which are different in function. The former is a low frequency vibration detector whereas the latter functions as an ion receptor as well as a mechano receptor.The fine structure of the sensory epithelia of both organs were studied by means of ordinary transmission electron microscope, high voltage electron microscope and of surface scanning electron microscope.The sensory cells of the canal organ are polarized in front-caudal direction and those of the pit organ are polarized in dorso-ventral direction. The sensory epithelia of both organs have thinner surface coats compared to the surrounding ordinary epithelial cells, which have very thick fuzzy coatings on the apical surface.


Author(s):  
Robert E. Nordquist ◽  
J. Hill Anglin ◽  
Michael P. Lerner

A human breast carcinoma cell line (BOT-2) was derived from an infiltrating duct carcinoma (1). These cells were shown to have antigens that selectively bound antibodies from breast cancer patient sera (2). Furthermore, these tumor specific antigens could be removed from the living cells by low frequency sonication and have been partially characterized (3). These proteins have been shown to be around 100,000 MW and contain approximately 6% hexose and hexosamines. However, only the hexosamines appear to be available for lectin binding. This study was designed to use Concanavalin A (Con A) and Ricinus Communis (Ricin) agglutinin for the topagraphical localization of D-mannopyranosyl or glucopyranosyl and D-galactopyranosyl or DN- acetyl glactopyranosyl configurations on BOT-2 cell surfaces.


Author(s):  
P. A. Marsh ◽  
T. Mullens ◽  
D. Price

It is possible to exceed the guaranteed resolution on most electron microscopes by careful attention to microscope parameters essential for high resolution work. While our experience is related to a Philips EM-200, we hope that some of these comments will apply to all electron microscopes.The first considerations are vibration and magnetic fields. These are usually measured at the pre-installation survey and must be within specifications. It has been our experience, however, that these factors can be greatly influenced by the new facilities and therefore must be rechecked after the installation is completed. The relationship between the resolving power of an EM-200 and the maximum tolerable low frequency interference fields in milli-Oerstedt is 10 Å - 1.9, 8 Å - 1.4, 6 Å - 0.8.


Author(s):  
G. Y. Fan ◽  
J. M. Cowley

It is well known that the structure information on the specimen is not always faithfully transferred through the electron microscope. Firstly, the spatial frequency spectrum is modulated by the transfer function (TF) at the focal plane. Secondly, the spectrum suffers high frequency cut-off by the aperture (or effectively damping terms such as chromatic aberration). While these do not have essential effect on imaging crystal periodicity as long as the low order Bragg spots are inside the aperture, although the contrast may be reversed, they may change the appearance of images of amorphous materials completely. Because the spectrum of amorphous materials is continuous, modulation of it emphasizes some components while weakening others. Especially the cut-off of high frequency components, which contribute to amorphous image just as strongly as low frequency components can have a fundamental effect. This can be illustrated through computer simulation. Imaging of a whitenoise object with an electron microscope without TF limitation gives Fig. 1a, which is obtained by Fourier transformation of a constant amplitude combined with random phases generated by computer.


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